… In order to obtain high-level emotion recognition of each facial image, we adopt a CNN
architecture for emotion classification. The structure of the classifier can be briefly shown as Fig. 3…

… Facial emotion recognition (FER) is significant for human-computer interaction such as
clinical practice and behavioral description. Accurate and robust FER by computer models …

… a robust feature extraction method for mobile-based speech emotion recognition system. A
… Then a robust feature extraction method called SFS feature optimization is implemented to …

… can influence the accuracy of recognition as a consequence of signal magnification. Therefore,
in this paper a robust speech emotion recognition system that uses a robust feature, log …

… In addition, the deep BiLSTM model improved emotion recognition from EGG through the
extraction of discriminative features and temporal dependencies of speech samples. However, …

… emotion classification challenge, which mimics the real-world conditions. Traditionally, emotion
recognition … to explore the performance of emotion recognition methods that work `in the …

… as robust representation and classification techniques. With the increase in the number of
video clips online, it is worthwhile to explore the performance of emotion recognition methods …

… robust interaction between machines and humans. In this paper, we review CNNbased
methods for facial emotion recognition … APIs for facial emotion recognition. Index Terms—Facial …

… of emotion recognition via words, as in more recent works [1,8], emotional state models
included lists of all emotional … We also consider the case of emotion recognition via sentences, …

… in emotion recognition through both audio and visual data. … In addition, we will further
investigate the robustness of the … of these behaviours to the accuracy of emotion recognition. …